Evolution of Ontologies and Types

ISBN: 978-972-8924-68-3International audienceOntologies are heavily used in the context of the Semantic Web (Berners-Lee 1998, 2001) to formalize human knowledge. Ontologies engineering is now an important activity, and specialized softwares are developed to help in managing huge ontologies. The development of ontologies and of information systems can be compared to the development of programs. In this paper we make a parallel between ontologies and types in programming languages, and we use a small example to show that an ontology can be seen as a type system. When an ontology evolves, studying the impact of this evolution on the semantic annotations that use this ontology can be viewed as a type-checking process. The next step should be to import some notions used in the types community as overloading, polymorphism, type parameters, etc. to improve or create more powerful ontology definition languages

Ontologies on the semantic web

As an informational technology, the World Wide Web has enjoyed spectacular success. In just ten years it has transformed the way information is produced, stored, and shared in arenas as diverse as shopping, family photo albums, and high-level academic research. The “Semantic Web” was touted by its developers as equally revolutionary but has not yet achieved anything like the Web’s exponential uptake. This 17 000 word survey article explores why this might be so, from a perspective that bridges both philosophy and IT

Intégration texte-représentation formelle pour la gestion de documents XML

DEA d'informatique, Université Joseph Fourier-INPG, Grenoble (FR) - troncy2000aActuellement, le Web contient d'importantes quantités d'informations couvrant tous les sujets imaginables. Le problème qui était avant de savoir si une information, même très spécifique, était disponible sur le Web, est mainte nant devenu comment retrouver cette information. Apporter du sens intelligible et exploitable par des machines aux documents devrait leur permettre d'utiliser l'information présente, d'améliorer les techniques de recherche, et donc de faire du Web une gigantesque base de connaissance. Les langages de représentation de connaissance sont de bons candidats si l'on souhaite décrire le contenu de documents. L'action Escrire a d'ailleurs pour objectif d'en comparer trois. Parmi eux, la représentation de connaissances à objets apparaît particulièrement adaptée lorsqu'il s'agit de représenter des connaissances complexes sur un domaine en cours d'étude. On pourra alors manipuler plus efficacement une base de documents en les indexant par leur contenu (ou leur sens). Les documents pertinents seront ramenés à partir de requêtes structurées tirant parti du formalisme de représentation de connaissance (hiérarchie de classes, mécanismes de classification...). Nous avons d'abord observé le lien étroit existant entre la nature de la connaissance à représenter et le type du document. Nous avons aussi pu voir que plus que le contenu, c'est l'application résultante qui va

Lessons Learned From Applying AI To The Web

Ontobroker applies Artificial Intelligence techniques to improve access to heterogeneous, distributed and semistructured information sources as they are presented in the World Wide Web or organizationwide intranets. It relies on the use of ontologies to annotate web pages, formulate queries and derive answers. In this paper we will briefly sketch Ontobroker. Then we will discuss its main shortcomings, i.e. we will share the lessons we learned from our exercise. We will also show how On2broker overcomes these limitations. Most important is the separation of the query and inference engines and the integration of new web standards like XML and RDF. Keywords: World Wide Wide, Internet, Information retrieval, Ontologies, Semantics 1. Introduction The World Wide Web (WWW) currently contains around 300 million static objects providing a broad variety of information sources (cf. [Bharat & Broder, 1998]). The early question of whether a certain piece of information is on the Web has be..

On2broker: Lessons Learned from Applying AI to the Web

Ontobroker applies Artificial Intelligence techniques to improve access to heterogeneous, distributed and semistructured information sources as they are presented in the World Wide Web or organization-wide intranets. It relies on the use of ontologies to annotate web pages, formulate queries and derive answers. In the paper we will briefly sketch Ontobroker. Then we will discuss its main shortcomings, i.e. we will share the lessons we learned from our exercise. We will also show how On2broker overcomes these limitations. Most important is the separation of the query and inference engines and the integration of new web standards like XML and RDF